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Depth statistics     Depth statistics       2012/9/19
In 1975 John Tukey proposed a multivariate median which is the ‘deepest’ point in a given data cloud in Rd(Tukey, 1975). In measuring the depth of an arbitrary pointzwith respect to the data, he consi...
In this paper, we show that the adaptive multidimensional increment ratio estimator of the long range memory parameter defined in Bardet and Dola (2012) satisfies acentral limit theorem (CLT in the se...
北京大学光华管理学院商务统计与经济计量系博士生常晋源近期在国际统计学最顶级的学术期刊The Annals of Statistics上发表了题为On the approximate maximum likelihood estimation for diffusion processes 的论文(第一作者)。
In this article, we study the fluctuations of the random variable: $$ {\mathcal I}_n(\rho) = \frac 1N \log\det(\Sigma_n \Sigma_n^* + \rho I_N),\quad (\rho>0) $$ where $\Sigma_n= n^{-1/2} D_n^{1/2} X_n...
This article provides a brief introduction to seven papers that are included in this special section on Statistics in Neuroscience: (1) Xiaoyan Shi, Joseph G. Ibrahim, Jeffrey Lieberman, Martin Styner...
We establish a simple variance inequality for U-statistics whose underlying sequence of random variables is an ergodic Markov Chain.
Riemannian statistics geometry is proposed in this work as a counterpart approach of inference geometry.
Detecting and locating changes in highly multivariate data is a major concern in several current statistical applications. In this context, the first contribution of the paper is a novel non-parametri...
This paper studies the change point problem for a general parametric, univariate or multivariate family of distributions.
Recently Batsidis \textit{et al.} (2011) have presented a new procedure based on divergence measures for testing the hypothesis of the existence of a change point in exponential populations.
Simulation has become a standard tool in statistics because it may be the only tool available for analysing some classes of probabilistic models. We review in this paper simulation tools that have be...
A new approach to adaptive design of clinical trials is proposed in a general multi- parameter exponential family setting, based on generalized likelihood ratio statistics and optimal sequential tes...
This paper presents a new methodology to solve problems resulting from missing data in large-scale item performance behavioral databases. Useful statistics corrected for missing data are described, an...
Using a recently developed model, inspired by mean field theory in statistical physics, and data from the UK's Research Assessment Exercise, we analyse the relationship between the quality of statisti...
This paper presents a new methodology to solve problems resulting from missing data in large-scale item performance behavioral databases. Useful statistics corrected for missing data are described, an...

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